The proposed studies have several closely related aims that revolve around the broader goal of determining the mechanisms by which infants and very young children start to classify the words in their language. Determining how words are classified is a crucial part of learning the structure of a language on any theory of language acquisition. The fundamental hypothesis investigated in this proposal is that young language learners perform a distributional analysis on their linguistic input, and classify words together which occur in the same kinds of distributional environments (e.g., following a, the and happy, and preceding sings, sleep, knows, etc.). Distributional information is present in every utterance a child hears, and could provide a rich source of information about the basic categories of the language. This proposal investigates these questions with three multi-experimental studies. Study 1 undertakes an analysis of the distributional environments that are most informative for noun and verb classification, and attempts to link these environments with children's own utterances. Study 2 investigates whether 12-13-month-old infants use distributional information to categorize words in two ways: Study 2.1 tests for distributional categorization mechanisms by using English sentences, and Study 2.2 further tests the parameters of these mechanisms using artificial languages. Finally, Study 3 explores 14-15 month old infants use of distributional patterns of inflections to classify words. Taken together, the results of these studies will greatly increase our understanding of the nature of infants' any young children's crucial, early, stages of grammatical representations, and how they acquired them. Thus, the debate about the role of distributional analyses in children's early category representations can shift from the domain of speculation to that of empirical investigation.